| Increase the Lifetime of Wireless Sensor Networks by Minimizing Energy Consumption When Selecting Cluster Head uses Meta-Heuristic Algorithms |
| Pages: 252-258 (7) | [Full Text] PDF (317 KB) |
| M Sedighimanesh, A Sedighimanesh, J Baqeri |
| Department of Electrical, Computer and IT Engineering, Islamic Azad University of Qazvin, Qom, Iran |
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Abstract - A wireless sensor network, consist of a large number of the sensor nodes, which are distributed in a particular area, that each of them has an ability to collect information from the environment and sending data collected to the base station.Wireless sensor networks are severely limited resources, limited resources, including the amount of energy, short communication range, low bandwidth,limited memory and processing in each sensor. Hence the use of clustering algorithm that would reduce energy consumption and leads to bandwidth appropriate efficiency, is critical. In this paper ,we are studying LEACH, and ELEACH algorithms. And then we proposed a clustering approach using PSO(Particle swarm optimization) meta heuristic algorithm. The proposed algorithm is examined by simulation of MATLAB that simulation results in heterogeneous environments show that the proposed algorithm improved the network lifetime by more or less 75% than LEACH protocol, and approximately 55% compared to ALEACH. |
| Index Terms - Wireless Sensor Networks, Lifetime, Hierarchical Clustering, Particle Swarm Algorithm |
C itation - M Sedighimanesh, A Sedighimanesh, J Baqeri. "Increase the Lifetime of Wireless Sensor Networks by Minimizing Energy Consumption When Selecting Cluster Head uses Meta-Heuristic Algorithms." International Journal of Computer Networks and Communications Security 4, no. 9 (2016): 252-258. |
| Towards proposing network topology for improving performance in Plateau State University Bokkos |
| Pages: 259-264 (6) | [Full Text] PDF (264 KB) |
| DK Aristarkus, S Palaniappan,T Purnshatman |
| Plateau State University Bokkos, Nigeria Malaysian University of Science and Technology, Malaysia |
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Abstract - This paper is concerned with the computer network of Plateau State Universities Bokkos, which is located in Plateau State, Nigeria, in the western part of Africa. The existing network topology of Plateau State University Bokkos (PSU) is being investigated via interview method of survey. With the help of the Technical Staff the University, information about the topology will be collected and/or confirmed via observation. The confirmed topology or layout will be design and simulated for behavioural outputs. Then, the outputs of the simulation of the two topologies will be analyzed, towards proposing a better topology for improving performance. CISCO Packets Tracer simulator will be used for all necessary designs and simulation. In the end a suitable topology requirement will be proposed for improving network performance in Plateau State University, being a newly established University. |
| Index Terms - Campus Area Network, Network Simulation, Comparative Analysis |
C itation - DK Aristarkus, S Palaniappan,T Purnshatman. "Towards proposing network topology for improving performance in Plateau State University Bokkos." International Journal of Computer Networks and Communications Security 4, no. 9 (2016): 259-264. |
| Segmentation and Classification Customer Payment Behavior at Multimedia Service Provider Company with K-Means and C4.5 Algorithm |
| Pages: 265-275 (11) | [Full Text] PDF (766 KB) |
| S Moedjiono, F Fransisca, A Kusdaryono |
| Master of Computer Science, Budi Luhur University, Jakarta, Indonesia |
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Abstract - Multimedia internet and television (tv) cabel service provider companies get problem with customer who refuse to pay after using the service. Its hard to identify solvency customer because service provider companies do not do customer finance verification. This research use model with join k-means segmentation and C4.5 classification algorithm because C4.5 weaknesses in difficulty to choose attributes. Be proven that extract customer potential attributes with k-means can help to increase C4.5 classification algorithms accuracy. This thing proved from the model accuracy increment from 59.02% to 77.31% and AUC from 0.537 to 0.836. Customer potential level can also be the reference in promotion, retention, and prevention of insolvency customer. |
| Index Terms - Customer loyalty, C4.5 Algorithm, K-means Algorithm, Multimedia Company, Data Mining |
C itation - S Moedjiono, F Fransisca, A Kusdaryono. "Segmentation and Classification Customer Payment Behavior at Multimedia Service Provider Company with K-Means and C4.5 Algorithm." International Journal of Computer Networks and Communications Security 4, no. 9 (2016): 265-275. |